The present invention is directed to a system and an appertaining method for determining and outputting parameters associated with an ear canal according to a particular taxonomy. The output can then be input to various other systems associated with hearing aid design. More specifically, the present invention utilizes an intelligent computational approach that models the physiology of the human ear canal as reconcilable with a conic or quadric section. Furthermore the output parameters establish a fundamental basis for designing automated 3D design software for hearing instrument design and manufacturing. In the absence of structured classification protocols for human ear canals, algorithms designed to automate design of hearing instruments are usually not robust and are unstable.
This instability is directly related to the inability to develop one system of algorithms for multiple ear canals shapes and complexity associated with any given human population sample. The present invention provides a method and process that allows human ear canals to be classified based on measurement of geometric variability along extracted molds of hearing aid impression. The methods advanced herein further ensure an automated classification of all human ear canal shapes can be implemented.
Hearing aid design involves the creation of hearing aid shells that are shaped to match the wearers ear for purposes of comfort and performance. An important part of the shell design relates to the ear canal and the aspects of the shell that relate to it.
Computer modeling of the ear, based on impressions taken from the wearer's ear, and the corresponding shell design based on these impressions is becoming a standard mechanism in the production of hearing aids.